vulcan {vulcan} | R Documentation |
This function calculates the enrichment of a gene regulatory network over a ChIP-Seq derived signature
vulcan(vobj, network, contrast, annotation = NULL, minsize = 10)
vobj |
a list, the output of the |
network |
an object of class |
contrast |
a vector of two fields, containing the condition names to be compared (1 vs 2) |
annotation |
an optional named vector to convert gene identifiers (e.g. entrez ids to gene symbols) Default (NULL) won't convert gene names. |
minsize |
integer indicating the minimum regulon size for the analysis to be run. Default: 10 |
A list of components:
A matrix of raw peak counts, peaks as rows, samples as columns
A matrix of peak RPKMs, peaks as rows, samples as columns
A matrix of raw gene counts, genes as rows, samples as columns. The counts are associated to the promoter region of the gene
A matrix of RPKMs, genes as rows, samples as columns. The RPKMs are associated to the promoter region of the gene
A matrix of gene abundances normalized by Variance-Stabilizing Transformation (VST), genes as rows, samples as columns. The abundances are associated to the promoter region of the gene
A vector of sample names and conditions
a multisample virtual proteomics object from the viper package
A table of master regulators for a specific signature, indicating their Normalized Enrichment Score (NES) and p-value
library(vulcandata) # Get an example vulcan object (generated with vulcan.import() using the # dummy dataset contained in the \textit{vulcandata} package) vobj<-vulcandata::vulcanexample() # Annotate peaks to gene names vobj<-vulcan.annotate(vobj,lborder=-10000,rborder=10000,method='sum') # Normalize data for VULCAN analysis vobj<-vulcan.normalize(vobj) # Detect which conditions are present names(vobj$samples) # Load an ARACNe network # This is a regulon object as specified in the VIPER package, named 'network' load(system.file('extdata','network.rda',package='vulcandata',mustWork=TRUE)) # Run VULCAN # We can reduce the minimum regulon size, since in this example only one # chromosome # was measured, and the networks would otherwise have too few hits vobj_analysis<-vulcan(vobj,network=network,contrast=c('t90','t0'),minsize=5) # Visualize output using the msviper plotting function plot(vobj_analysis$msviper,mrs=7)